389 results about "Binary tree" patented technology

Techniques are described for a hierarchical caching mechanism enabling efficient cross-region replications. In some embodiments, replication-related information (e.g., key-value pairs) is stored in a particular layout in a binary tree (B-tree) of a file system for replication processing. A hierarchy of caches storing a first type of information (e.g., crypto keys associated with iNodes) may be arranged to match the particular layout in the B-tree to enable efficient parallel processing of a second type of information (e.g., files, file data, or symbolic links), where the replication-related information in the B-tree is partitioned into multiple key ranges for parallel processing. In some embodiments, the caches in different hierarchies may be shared by different parallel-processing key ranges and replication jobs in a file system.

The invention relates to a bridge structure vibration monitoring and analysis method based on artificial intelligence, and the method specifically comprises the following steps: setting an acceleration sensor network at a key part of a bridge, collecting and marking a vibration signal sample, and forming a data set; a high-resolution time-frequency matrix of sample adaptive optimal kernel time-frequency distribution is calculated, a damage sensitive resonance frequency band is positioned according to spectrum kurtosis, and the time-frequency matrix is enhanced by the resonance frequency band subjected to adaptive gain enhancement; dividing a matrix frequency axis multi-scale binary tree, calculating and normalizing sub-band average energy, quantifying energy distribution uniformity through information entropy, and splicing multi-scale entropy values into feature vectors; then constructing and training a bridge detection data model; and finally, preprocessing new data, inputting the preprocessed new data into the trained model, and automatically analyzing to obtain a bridge health monitoring result. Through time-frequency optimization, multi-scale entropy and deep learning technologies, the problems of large noise, difficult feature extraction and low automation and accuracy of traditional monitoring can be solved.

The invention discloses a decentralized identity management method based on a trusted execution environment, and the method comprises the steps: generating, isolating and storing a user decentralized identity in the trusted execution environment of equipment, carrying out the Hash signature of a decentralized identity document, and recording an uplink; the block chain consensus node verifies the decentralized document uplink transaction through a Byzantine fault-tolerant consensus mechanism and achieves consistency, and writes the metadata of the decentralized identity into the block; encrypting and storing the voucher in a trusted execution environment of the equipment by adopting a Pearson commitment, and supporting voucher Hash uplink and commitment uplink; and introducing a multilevel access structure based on a binary tree, and verifying the and / or logic combination voucher by adopting a depth-first search algorithm. According to the method, decentralized autonomy of the user identity and hardware security isolation are supported, and the reliability and privacy protection capability of user identity management are improved.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention discloses a distributed job scheduling method and device, a storage medium and computer equipment, relates to the technical field of distributed task scheduling, is suitable for the field of financial and medical services, and mainly aims at solving the problem that an existing distributed job scheduling system lacks task dependence management and dynamic scheduling capability. Comprising the following steps: performing task modeling processing on each to-be-executed task by adopting a binary tree structure to obtain a task binary tree corresponding to each to-be-executed task; performing serialization processing on the task binary tree by adopting a job arrangement engine to obtain a corresponding task sequence; issuing the task sequence to an event flow bus; after the event flow bus is started, tasks to be executed are allocated to different distributed actuators for execution based on the central control scheduler; and the distributed executor returns an execution result to the event flow bus in real time, so that the event flow bus triggers the downstream task after the upstream task is completed until the task sequence is completely executed.

The invention relates to the technical field of distributed data processing systems, and discloses a data processing system supporting full localization deployment and a compliance guarantee method thereof.The data processing system supporting full localization deployment comprises an audit event collection module used for collecting and storing processing event hash; the event organization module is used for realizing logic time sequence management of events through topological sorting and causal relationship marking; the hash chain construction module is used for constructing a local-to-global double-layer hash chain by utilizing the constructed directed acyclic graph and event hash; the increment synchronization module is used for executing increment synchronization based on Hash tree difference identification; the conflict solving module is used for detecting and solving event conflicts in the distributed environment by applying a version vector technology aiming at data differences found in the incremental synchronization process; according to the method, the lightweight linear hash chain is used for replacing a traditional binary tree structure, high-efficiency and low-cost audit chain maintenance is realized, and the data integrity is guaranteed in an unstable network environment.

The invention relates to the technical field of artificial intelligence chips and storage management, in particular to a cache line replacement method and device, a chip and electronic equipment. The method is applied to a chip comprising a data cache, the data cache comprises N cache lines in which data are stored, an access path corresponding to each cache line is managed based on a binary tree structure comprising N-1 nodes in a PLRU algorithm, and a data replacement instruction is responded, obtaining a path status bit from a root node to a leaf node on an access path corresponding to each cache line; for a specified cache line, calculating a PLRU path value according to the path status bit, and calculating a replacement score in combination with the importance level and the corresponding weight of the stored data; determining a replaceable cache line according to the replacement score; and storing the to-be-cached data and the importance level thereof into a replaceable cache line to replace the original data and the original level. Therefore, the cache line replacement priority is evaluated by combining the PLRU path value and the importance level of the stored data, the cache hit rate is effectively improved, and the system performance is optimized.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention discloses a signal transmission method, a signal receiving method, a channel sending end and a channel receiving end, and belongs to the technical field of communication, and the signal transmission method comprises the steps: obtaining to-be-sent original data, and generating a bit encryption factor, a constellation encryption factor, a bit disturbance factor and a constellation disturbance factor; the method comprises the following steps: dividing original data to be sent into even number of data blocks according to a preset rule to construct a complete binary tree, and carrying out first traversal encryption and primary disturbance on the data blocks by utilizing a bit encryption factor; converting the data block subjected to primary perturbation into a parallel bit stream through serial-parallel conversion, performing QAM mapping on the parallel bit stream, and performing second traversal encryption and second perturbation according to a constellation perturbation factor; the parallel bit streams after secondary disturbance are converted into serial signals through a discrete Fresnel inverse transformation matrix and parallel-serial conversion; and performing up-conversion processing on the serial signal and transmitting the serial signal to a transmission channel. According to the invention, the problem of insufficient safety protection in practical application in the prior art is solved.

The invention discloses a log auditing method, system and device, electronic equipment and a medium, and relates to the technical field of information security, and the log auditing method comprises the following steps: performing fragmentation processing on an original log according to a preset fragmentation condition to obtain at least two target log fragments; based on the target log fragment, determining a target hash value corresponding to the target log fragment, the target hash value being a node value of a root node in a binary tree determined by the target log fragment; the target hash value is written into a block chain, the target hash value in the block chain is used for determining a log auditing result, and the technical problem that in a related log auditing scheme, logs on a centralized storage system are easily modified and deleted by internal personnel, and then the log auditing result is incredible is solved; the technical effect of improving the credibility of the audit result is achieved.

This application relates to apparatus and methods for generating and implementing a machine learning model in electronic delivery systems to determine delivery routes and times. In some examples, a computing device generates a machine learning model comprising a plurality of indexed binary trees. Each indexed binary tree determines either a first value, or a second value, based on comparing an input to a condition value. The machine learning model can generate prediction values based on the determined values of all indexed binary trees. The machine learning model is trained with historical data. Once trained, the machine learning model's performance is evaluated. Based on the evaluation, the machine learning model may be further refined. Once the machine learning model's performance satisfies requirements, the computing device employs the machine learning model to determine vehicle delivery routes and estimated delivery times.

The invention discloses a distribution network terminal topology identification and distance measurement method and system, and the method comprises the steps: generating a binary tree according to the data of a tower, a switch, a line and the like, determining a reference terminal and an effective terminal according to the wave head moment data after the line breaks down, carrying out the topology identification through employing a binary tree algorithm, positioning a fault section, and carrying out the distance measurement. The method can adapt to topological changes caused by switch position changes, and is small in calculation amount and easy to implement.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention provides a multi-medical image encryption method with tampering localization capability, and aims to solve the problems of security and integrity of digital medical images in transmission and storage, and the core is to provide localized tampering prevention capability. According to the method, firstly, a novel two-dimensional S-type logarithmic chaotic mapping 2D-SLCM is utilized to generate a secret key and a chaotic sequence which are highly related to plaintext content so as to resist differential attacks; then, performing efficient compression on each medical image by adopting a block compressed sensing (BCS) technology to ensure the transmission efficiency; in the encryption stage, data confidentiality is ensured through a multi-layer encryption process including local binary tree traversal scrambling and global random block scrambling; most importantly, an encrypted unique digital watermark is embedded into each image before the images are merged; the dual mechanism not only can detect the tampering behavior, but also can accurately identify which image in the multi-image set is damaged by verifying the watermark extracted from each image, thereby ensuring the reliability of residual data.

The invention discloses an ALB sounding point cloud filtering and recovering method for complex terrains such as a submarine abrupt slope, belongs to the technical field of data processing, and solves the problems that the I-class misjudgment rate is high, topographic features are smoothed or weakened and effective point clouds at the submarine abrupt slope are easily filtered out excessively in an existing method. The method comprises the steps of performing sea surface elevation estimation and separation processing on original point cloud, processing underwater point cloud based on a self-adaptive morphology water body filtering method, introducing a recovery mechanism based on hyperboloid fitting, recovering abrupt slope area point cloud misjudged as a water body noisy point through residual analysis, and obtaining a water body noisy point. According to the method, a fine processing strategy of filtering first and then recovering is adopted, and water body noisy points are accurately removed through self-adaptive morphological filtering in the earlier stage in combination with grid reference surface and spatial multi-dimensional binary tree index neighborhood analysis. A recovery mechanism based on hyperboloid fitting is introduced, and the abrupt slope area point cloud misjudged as the noisy point is recovered through residual analysis. And the misjudgment rate in a submarine abrupt slope area is effectively reduced.

Methods, systems, and devices for coding or decoding video wherein the picture partition mode is based on block size are described. An example method for video processing includes using a dimension of a virtual pipeline data unit (VPDU) used for a conversion between a video comprising one or more video regions comprising one or more video blocks and a bitstream representation of the video to perform a determination of whether a ternary-tree (TT) or a binary tree (BT) partitioning of a video block of the one or more video blocks is enabled, and performing, based on the determination, the conversion, wherein the dimension is equal to VSize in luma samples, wherein dimensions of the video block are CtbSizeY in luma samples, wherein VSize=min(M, CtbSizeY), and wherein M is a positive integer.

The invention discloses a light quantum chip which is combined with high-dimensional coding, is provided with two data coding layers and two trainable entanglement layers, is compatible with a data recoding technology, and can be used for variable component subtasks such as a quantum neural network. The chip structure comprises a cascaded Mach-Zehnder interferometer binary tree array, d groups of photon pair sources, d groups of controlled unitary gate modules, a multi-quantum bit control Z gate, four d-dimensional adjustable linear networks and two state tomography linear networks. The cascaded MZI binary tree array and the controlled unitary group jointly form a first coding layer and a parameter-containing entanglement layer, and the adjustable optical linear network and the multi-quantum bit control Z gate jointly form a second coding layer and a parameter-containing entanglement layer. The two state chromatography linear networks can further improve the computing power of the chip in a mode of changing a measurement basis or executing quantum state chromatography. According to the method, the expression ability of the light quantum neural network is improved, and the development of a light quantum computing chip and the application of the light quantum computing chip in actual tasks are facilitated.

A method of partitioning in video coding for JVET, comprising representing a JVET coding tree unit as a root node in a quadtree plus binary tree (QTBT structure that can have quadtree or binary partitioning of the root node and quadtree or binary trees branching from each of the leaf nodes. The partitioning at any depth can use asymmetric binary partitioning to split a child node represented by a leaf node into two child coding units of unequal size, representing the two child coding units as leaf nodes in a binary tree branching from the parent leaf node and coding the child coding units represented by final leaf nodes of the binary tree with JVET. Disclosed is a generalized method of partitioning a block, either square or rectangular, which leads to more flexible block sizes with possible higher coding efficiency.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The present application relates to the technical field of video coding, and especially relates to a coding unit division fast decision method and system based on multi-functional video coding, comprising constructing a quadtree division prediction network, using the network to judge whether a coding tree unit needs to perform quadtree division, and obtaining a coding unit after performing the quadtree division; constructing a mixed tree division prediction network, using the network to judge whether the coding unit needs to be divided, stopping division if the coding unit does not need to be divided, otherwise judging whether the coding unit adopts binary tree division or ternary tree division, and taking a smaller coding unit division prediction value in parallel branches as a final prediction result. The present application improves coding efficiency, and can balance the relationship between visual quality and coding efficiency by selecting different threshold values according to specific scene needs.

The present invention discloses a document intelligent parsing method and system, which is executed by a document intelligent parsing system. The method includes the following steps: using a deep learning model to perform layout analysis on PDF pages; using a recursive algorithm to merge the block lists from bottom to top; optimizing the balance of the binary tree structure; and outputting the result of the processed binary tree structure using a pre-order traversal method. By using a deep learning model to perform layout analysis, it is possible to effectively identify and process various complex typesetting formats such as multi-column layouts, mixed text and image layouts, tables, lists, etc., using a tree structure optimization module to ensure that semantically continuous text blocks also maintain continuity in the tree structure, and by adding a global semantic error correction module to perform global document semantic representation learning, adaptively adjust and correct the preliminary structure, thereby eliminating deep ambiguity, repairing logical errors, and maximizing the consistency of the final parsing result with human reading logic at the semantic level.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention provides a video coding method, which comprises the following steps of: inputting a coding tree unit to be coded, and extracting texture features of a coding block, the texture features comprising local binary pattern similarity of all pixel points in the coding block and direction dispersion of each pixel point; inputting the texture features into the trained multi-type division prediction architecture, and sequentially judging whether to execute quadtree division, horizontal or vertical division, horizontal binary tree or ternary tree division and vertical binary tree or ternary tree division or not through a binary classification problem method; and calculating the rate distortion cost under each division mode to obtain an optimal division mode and a suboptimal division mode of the coding block, and outputting an optimal mode or a combination of the optimal mode and the suboptimal mode. According to the invention, the accuracy of the prediction mode in coding is improved.

The application discloses an inadvertent random access machine storage system based on a double-buffer data read-write algorithm, which comprises a cloud storage unit and a user end, wherein the cloud storage unit is provided with a full binary tree for storing encrypted data; the user end is provided with a first buffer, a second buffer and a position table located at the user end; a part of the top of the full binary tree is not used for storing data, so that the full binary tree comprises m full binary tree sub-trees.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

Disclosed are methods and apparatuses for decoding an image. A method includes receiving a bitstream obtained by encoding the image; dividing a first coding block into a plurality of second coding blocks; generating a prediction block of a second coding block based on syntax information obtained from the bitstream; and reconstructing the second coding block based on the prediction block and a residual block of the second coding block, the residual block being obtained by performing a dequantization and an inverse-transform on quantized transform coefficients from the bitstream. The first coding block has a recursive division structure. The first coding block is divided based on at least one of a quad tree division, a binary tree division or a triple tree division.

The invention provides a double-server combined keyword dynamic searchable encryption method with forward and backward security, which is applied to a system comprising a data owner, a data user, a first server and a second server. Keywords and associated file identifiers are stored in each leaf node, information of non-leaf nodes is mapped to a non-distinguishable long filter, and through a random state updating mechanism, a keyword double-state array and a time factor trap door design, it is guaranteed that keyword joint search is achieved, and meanwhile, the information of the non-leaf nodes can be quickly and efficiently searched. And the forward safety and the backward safety are also ensured. According to the dual-server architecture, security index storage and trap door verification are separated, so that the problem of KPRP leakage is effectively relieved.

In some implementations, a memory apparatus may receive a command indicating a logical block address (LBA) that is associated with a logical-to-physical (L2P) table. The memory apparatus may perform a lookup operation associated with a compressed version of an address range of the L2P table to identify a physical address in non-volatile memory associated with the LBA, wherein the compressed version is stored in a volatile memory of the memory apparatus, wherein the compressed version is associated with an exception list that indicates physical addresses for respective LBAs, included in the address range, that are associated with non-sequential physical addresses, and wherein the compressed version is associated with a binary tree that indicates locations in the exception list associated with the respective LBAs. The memory apparatus may perform, based on the command, an action associated with the physical address.